Comment by troupo

> having to answer for opinions with no basis in the literatu

Having only literature on your side must feel nice.

> They have access to the full transcript, and they have access to the full codebase, the diff history, whatever knowledge base is available.

Yes. And it means that they don't learn, and they alway miss important details when rebuilding the world.

That's why even the tiniest codebases are immediately filled with duplications, architecturally unsound decisions, invalid assumptions etc.

> also not an accurate understanding of how agents and their context work; you can use multiple session to digest and distill information useful in other sessions and in fact

I say: agents don't learn and have to rebuild the world from scratch

You: not an accurate understanding of how agents and their context work.... they rebuild the world from scratch every time they run.

> You keep dismissing this literature as if you have understood it

No. I'm dismissing your flawed interpretation of purely theoretical constructs.

Chinchilla doesn't project unlimited amazing scalability. If anything, it shows a very real end of scalability.

Anthropic's paper adopts a nice marketable term for a process that has little to do with learning.

Etc.

Meanwhile you do keep rejecting actual real-world behaviour of these systems.

> Then are you arguing this progress will stop? I'm just not sure I understand, you seem to contradict yourself

I didn't say that either. Your opponents don't contradict themselves if you only stop to pretend they think or say.

Your unsubstantiated belief is that improvements are on a steep linear or even exponensial progression. Because "literature" or something.

Looking past all the marketing bullshit, it could be argued that growth is at best logarithmic, and most improvments come from tooling around (harnesses, subagents etc.). While all the failure modes from a year ago are still there: misunderstanding context, inability to maintain cohesion between sessions, context pollution etc.

And providers are running into the issue of getting non-polluted trainig data.

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At this point we're going around in circles, and I'm no interested in arguing with theorists.

Adieu